博碩士論文 102331015 詳細資訊




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姓名 劉庭嘉(Ting-Jia Liu)  查詢紙本館藏   畢業系所 生物醫學工程研究所
論文名稱 中風患者在復健後的大腦神經連結的變化
(The changes of neuronal dynamics in response to rehabilitation after stroke)
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摘要(中) 中風會造成患者癱瘓,尤其是上肢功能喪失而無法自理生活,復健治療的目的即為恢復其功能。對於大腦在中風後,是否會因為復健而有所不同的變化,已有許多學者利用腦電圖(electroencephalograph、EEG)、腦磁圖(magnetoencephalography、MEG)和磁振造影(MRI)等技術並且配合探討相關性的運算方法研究其變化,然而,前面文獻中的實驗動作主要以手指動作為主,我們好奇是否在以大動作(如抬手臂)為主也會有類似的結果,此外,腦波中不同的頻率成分在運動中亦扮演不同角色,而這頻率成分是否會因為復健而有所不同的變化也未曾被討論過。所以本研究的目的在於探討中風病患在復健之後的大腦不同的頻率成分功能性連結的變化,我們收集16位中風病患復健前與復健後的80次抬手臂動作腦電圖,每位病患的單次動作腦電圖透過小波轉換區分成三種頻帶(α band、β band、γ band)後依照時間點切割成5個窗格,使用互信息流與bi-serial correlation coefficient這兩種方法比較病患復健前與復健後的差異性,研究結果為所有病患之腦電圖頻道與其他頻道的功能性連結在復健後有下降的趨勢,顯示復健後大腦的神經網路之重組已經趨於穩定,而使用不同的復健方式所影響的功能性連結變化量會因為不同頻帶(α band和β band)而有所不同;且這些功能性連結的變化量在不同的時間窗格下之變化也有顯著的差異。
摘要(英) Motor deficits of the affected upper limb after stroke after up to two-thirds of stroke patients and conventional rehabilitation aims at reducing upper limb impairment , but significant variability exists between patients regarding rehabilitation efficacy. To date , the mechanisms induced by rehabilitation that can mediate the recovery process are not fully understood. What is brain after stroke change by rehabilitation? Recently , many experts used technologies (electroencephalograph, magnetoencephalography, magnetic resonance imaging, etc.) and correlation methods to investigate the change of rehabilitation. In these literatures, motor-task in methods was mainly finger motor. We are curious about whether the similar results between upper limb motor task and finger motor task or not. Moreover, difference frequency bandwidths of brain oscillation are played difference roles in motor separately .But it has not been discuss yet whether the change is difference of frequency bandwidths after rehabilitation or not. In this study , we discuss the functional connective changes of patients’ brain in different frequency bandwidths after rehabilitation. 16 stroke were recruited and underwent a conventional or virtual reality rehabilitation program with the frequency of 1 hour per day, five days a week. Before and after the rehabilitation, EEG data. EEG data was processed using the Morlet wavelet trans-
formation to generate the time-frequency representation of signals. Time-frequency maps after Morlet wavelet encompassing the α(8-12 Hz),β(16-25Hz) and γ(25-45 Hz) activities were created separately by averaging across trails and divided into 5 time windows. We used mutual information and bi-serial correlation coefficient to compared with functional connective changes before and after rehabilitation. We found that patients′ functional connectivity was decrease after rehabilitation. Because the reorganization of brain network was tended to be stable after rehabilitation. By difference rehabilitation, functional connective changes were difference in α band and β band. And in different windows, functional connective changes were significant difference.
關鍵字(中) ★ 互信息流
★ 腦電圖
★ 中風
★ 復健
關鍵字(英) ★ mutual information
★ EEG
★ stroke
★ rehabilitation
論文目次 摘要 i
Abstract ii
目錄 iv
圖目錄 v
表目錄 vi
第一章 背景知識與文獻回顧 1
1-1 中風與復健 1
1-2 復健與大腦可塑性 2
1-3 功能性連結(function connectivity) 3
第二章 緒論 6
2-1 研究動機 6
2-2 研究目的 6
2-3 論文架構 7
第三章 研究方法 8
3-1 受試者資料與實驗方法 8
3-2 訊號處理 10
第四章 實驗結果 14
第五章 討論與結論 27
第六章 未來展望 28
參考文獻 29
附錄 31
參考文獻 [1] P. Langhorne, J. Bernhardt, and G. Kwakkel, “Stroke rehabilitation,” The Lancet, vol. 377, no. 9778, pp. 1693–1702, 2011.
[2] Arya, K. N., Pandian, S., Verma, R., & Garg, R. K. (2011). Movement therapy induced neural reorganization and motor recovery in stroke: a review. Journal of bodywork and movement therapies, 15(4), 528-537.
[3] Richards, L. G., Stewart, K. C., Woodbury, M. L., Senesac, C., & Cauraugh, J. H. (2008). Movement-dependent stroke recovery: a systematic review and meta-analysis of TMS and fMRI evidence. Neuropsychologia, 46(1), 3-11.
[4] Taub, E., Uswatte, G., Mark, V. W., & Morris, D. M. (2006). The learlned nonuse phenomenon: implications for rehabilitation. Eura Medicophys, 42, 241-55.
[5] Belda-Lois, J. M., Mena-del Horno, S., Bermejo-Bosch, I., Moreno, J. C., Pons, J. L., Farina, D., ... & Caria, A. (2011). Rehabilitation of gait after stroke: a review towards a top-down approach. Journal of neuroengineering and rehabilitation, 8(1), 1.
[6] Mattar, A. A., & Gribble, P. L. (2005). Motor learning by observing. Neuron,46(1), 153-160.
[7] Merzenich, M. M., Kaas, J. H., Wall, J., Nelson, R. J., Sur, M., & Felleman, D. (1983). Topographic reorganization of somatosensory cortical areas 3b and 1 in adult monkeys following restricted deafferentation. Neuroscience, 8(1), 33-55.
[8] Buonomano, D. V., & Merzenich, M. M. (1998). Cortical plasticity: from synapses to maps. Annual review of neuroscience, 21(1), 149-186.
[9] Taub, E., Crago, J. E., Burgio, L. D., Groomes, T. E., Cook, E. W., DeLuca, S. C., & Miller, N. E. (1994). An operant approach to rehabilitation medicine: overcoming learned nonuse by shaping. Journal of the experimental analysis of behavior, 61(2), 281-293.
[10] Marshall, R. S., Perera, G. M., Lazar, R. M., Krakauer, J. W., Constantine, R. C., & DeLaPaz, R. L. (2000). Evolution of cortical activation during recovery from corticospinal tract infarction. Stroke, 31(3), 656-661.
[11] Nelles, G., Jentzen, W., Jueptner, M., Müller, S., & Diener, H. C. (2001). Arm training induced brain plasticity in stroke studied with serial positron emission tomography. Neuroimage, 13(6), 1146-1154.
[12] Shafi, M. M., Westover, M. B., Fox, M. D., & Pascual‐Leone, A. (2012). Exploration and modulation of brain network interactions with noninvasive brain stimulation in combination with neuroimaging. European Journal of Neuroscience, 35(6), 805-825.
[13] Wang, L., Yu, C., Chen, H., Qin, W., He, Y., Fan, F., ... & Woodward, T. S. (2010). Dynamic functional reorganization of the motor execution network after stroke. Brain, 133(4), 1224-1238.
[14] Cheng, L., Wu, Z., Sun, J., Fu, Y., Wang, X., Yang, G. Y., ... & Tong, S. (2015). Reorganization of Motor Execution Networks During Sub-Acute Phase After Stroke. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 23(4), 713-723.
[15] Li, W., Li, Y., Zhu, W., & Chen, X. (2014). Changes in brain functional network connectivity after stroke. Neural regeneration research, 9(1), 51.
[16] Shannon, C. E. (2001). A mathematical theory of communication. ACM SIGMOBILE Mobile Computing and Communications Review, 5(1), 3-55.
[17] David, O., Cosmelli, D., & Friston, K. J. (2004). Evaluation of different measures of functional connectivity using a neural mass model. Neuroimage,21(2), 659-673.
[18] Jeong, J., Gore, J. C., & Peterson, B. S. (2001). Mutual information analysis of the EEG in patients with Alzheimer′s disease. Clinical Neurophysiology, 112(5), 827-835.
[19] Chen, C. C., Hsieh, J. C., Wu, Y. Z., Lee, P. L., Chen, S. S., Niddam, D. M., ... & Wu, Y. T. (2008). Mutual‐information‐based approach for neural connectivity during self‐paced finger lifting task. Human brain mapping, 29(3), 265-280.
[20] Müller, K. R., Krauledat, M., Dornhege, G., Curio, G., & Blankertz, B. (2004). Machine learning techniques for brain-computer interfaces. Biomed. Tech,49(1), 11-22.
[21] Lu, C. F., Teng, S., Hung, C. I., Tseng, P. J., Lin, L. T., Lee, P. L., & Wu, Y. T. (2011). Reorganization of functional connectivity during the motor task using EEG time–frequency cross mutual information analysis. Clinical Neurophysiology, 122(8), 1569-1579.
指導教授 陳純娟(Chun-Chuan Chen) 審核日期 2016-8-29
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